SwePub
Sök i LIBRIS databas

  Utökad sökning

WFRF:(Sapisochin Gonzalo)
 

Sökning: WFRF:(Sapisochin Gonzalo) > The Toronto Postliv...

The Toronto Postliver Transplantation Hepatocellular Carcinoma Recurrence Calculator : A Machine Learning Approach

Ivanics, Tommy (författare)
Uppsala universitet,Gastrointestinalkirurgi,Univ OfToronto, Univ Hlth Network, Toronto Gen Hosp, Multiorgan Transplant Program,Div Gen Surg, Toronto, ON, Canada.;Henry Ford Hosp, Dept Surg, Detroit, MI 48202 USA.
Nelson, Walter (författare)
Centre for Data Science and Digital Health Hamilton Health Sciences Hamilton ON Canada;Department of Statistical Sciences University of Toronto Toronto ON Canada
Patel, Madhukar S. (författare)
Multi‐Organ Transplant Program Division of General Surgery Toronto General Hospital University Health Network University of Toronto Toronto Canada
visa fler...
Claasen, Marco P.A.W. (författare)
Multi‐Organ Transplant Program Division of General Surgery Toronto General Hospital University Health Network University of Toronto Toronto Canada;Department of Surgery Erasmus MC University Medical Center Rotterdam the Netherlands
Lau, Lawrence (författare)
Multi‐Organ Transplant Program Division of General Surgery Toronto General Hospital University Health Network University of Toronto Toronto Canada
Gorgen, Andre (författare)
Multi‐Organ Transplant Program Division of General Surgery Toronto General Hospital University Health Network University of Toronto Toronto Canada
Abreu, Phillipe (författare)
Multi‐Organ Transplant Program Division of General Surgery Toronto General Hospital University Health Network University of Toronto Toronto Canada
Goldenberg, Anna (författare)
SickKids Research Institute University of Toronto Toronto Canada
Erdman, Lauren (författare)
SickKids Research Institute University of Toronto Toronto Canada;Center for Computational Medicine SickKids Research Institute Toronto Canada
Sapisochin, Gonzalo (författare)
Multi‐Organ Transplant Program Division of General Surgery Toronto General Hospital University Health Network University of Toronto Toronto Canada
visa färre...
 (creator_code:org_t)
2021-11-05
2022
Engelska.
Ingår i: Liver transplantation. - : John Wiley & Sons. - 1527-6465 .- 1527-6473. ; 28:4, s. 593-602
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Liver transplantation (LT) listing criteria for hepatocellular carcinoma (HCC) remain controversial. To optimize the utility of limited donor organs, this study aims to leverage machine learning to develop an accurate posttransplantation HCC recurrence prediction calculator. Patients with HCC listed for LT from 2000 to 2016 were identified, with 739 patients who underwent LT used for modeling. Data included serial imaging, alpha-fetoprotein (AFP), locoregional therapies, treatment response, and posttransplantation outcomes. We compared the CoxNet (regularized Cox regression), survival random forest, survival support vector machine, and DeepSurv machine learning algorithms via the mean cross-validated concordance index. We validated the selected CoxNet model by comparing it with other currently available recurrence risk algorithms on a held-out test set (AFP, Model of Recurrence After Liver Transplant [MORAL], and Hazard Associated with liver Transplantation for Hepatocellular Carcinoma [HALT-HCC score]). The developed CoxNet-based recurrence prediction model showed a satisfying overall concordance score of 0.75 (95% confidence interval [CI], 0.64-0.84). In comparison, the recalibrated risk algorithms' concordance scores were as follows: AFP score 0.64 (outperformed by the CoxNet model, 1-sided 95% CI, >0.01; P = 0.04) and MORAL score 0.64 (outperformed by the CoxNet model 1-sided 95% CI, >0.02; P = 0.03). The recalibrated HALT-HCC score performed well with a concordance of 0.72 (95% CI, 0.63-0.81) and was not significantly outperformed (1-sided 95% CI, >= 0.05; P = 0.29). Developing a comprehensive posttransplantation HCC recurrence risk calculator using machine learning is feasible and can yield higher accuracy than other available risk scores. Further research is needed to confirm the utility of machine learning in this setting.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kirurgi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Surgery (hsv//eng)

Nyckelord

Transplantation
Hepatology
Surgery

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy